Co-targeting BET, CBP, and p300 inhibits neuroendocrine signalling in androgen receptor-null prostate cancer.

There are diverse phenotypes of castration-resistant prostate cancer, including neuroendocrine disease, that vary in their sensitivity to drug treatment. The efficacy of BET and CBP/p300 inhibitors in prostate cancer is attributed, at least in part, to their ability to decrease androgen receptor (AR) signalling. However, the activity of BET and CBP/p300 inhibitors in prostate cancers that lack the AR is unclear. In this study, we showed that BRD4, CBP, and p300 were co-expressed in AR-positive and AR-null prostate cancer. A combined inhibitor of these three proteins, NEO2734, reduced the growth of both AR-positive and AR-null organoids, as measured by changes in viability, size, and composition. NEO2734 treatment caused consistent transcriptional downregulation of cell cycle pathways. In neuroendocrine models, NEO2734 treatment reduced ASCL1 levels and other neuroendocrine markers, and reduced tumour growth in vivo. Collectively, these results show that epigenome-targeted inhibitors cause decreased growth and phenotype-dependent disruption of lineage regulators in neuroendocrine prostate cancer, warranting further development of compounds with this activity in the clinic. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Systematic Phenomics Analysis Deconvolutes Genes Mutated in Intellectual Disability into Biologically Coherent Modules.

Intellectual disability (ID) disorders are genetically and phenotypically extremely heterogeneous. Can this complexity be depicted in a comprehensive way as a means of facilitating the understanding of ID disorders and their underlying biology? We provide a curated database of 746 currently known genes, mutations in which cause ID (ID-associated genes [ID-AGs]), classified according to ID manifestation and associated clinical features. Using this integrated resource, we show that ID-AGs are substantially enriched with co-expression, protein-protein interactions, and specific biological functions. Systematic identification of highly enriched functional themes and phenotypes revealed typical phenotype combinations characterizing process-defined groups of ID disorders, such as chromatin-related disorders and deficiencies in DNA repair. Strikingly, phenotype classification efficiently breaks down ID-AGs into subsets with significantly elevated biological coherence and predictive power. Custom-made functional Drosophila datasets revealed further characteristic phenotypes among ID-AGs and specific clinical classes. Our study and resource provide systematic insights into the molecular and clinical landscape of ID disorders, represent a significant step toward overcoming current limitations in ID research, and prove the utility of systematic human and cross-species phenomics analyses in highly heterogeneous genetic disorders.

Arrestin-Domain Containing Protein 1 (Arrdc1) Regulates the Protein Cargo and Release of Extracellular Vesicles.

Extracellular vesicles (EVs) are lipid-bilayered vesicles that are released by multiple cell types and contain nucleic acids and proteins. Very little is known about how the cargo is packaged into EVs. Ubiquitination of proteins is a key posttranslational modification that regulates protein stability and trafficking to subcellular compartments including EVs. Recently, arrestin-domain containing protein 1 (Arrdc1), an adaptor for the Nedd4 family of ubiquitin ligases, has been implicated in the release of ectosomes, a subtype of EV that buds from the plasma membrane. However, it is currently unknown whether Arrdc1 can regulate the release of exosomes, a class of EVs that are derived endocytically. Furthermore, it is unclear whether Arrdc1 can regulate the sorting of protein cargo into the EVs. Exosomes and ectosomes are isolated from mouse embryonic fibroblasts isolated from wild type and Arrdc1-deficient (Arrdc1-/- ) mice. Nanoparticle tracking analysis-based EV quantitation shows that Arrdc1 regulates the release of both exosomes and ectosomes. Proteomic analysis highlights the change in protein cargo in EVs upon deletion of Arrdc1. Functional enrichment analysis reveals the enrichment of mitochondrial proteins in ectosomes, while proteins implicated in apoptotic cleavage of cell adhesion proteins and formation of cornified envelope are significantly depleted in exosomes upon knockout of Arrdc1.

Powerful differential expression analysis incorporating network topology for next-generation sequencing data.

MOTIVATION: RNA-seq has become the technology of choice for interrogating the transcriptome. However, most methods for RNA-seq differential expression (DE) analysis do not utilize prior knowledge of biological networks to detect DE genes. With the increased availability and quality of biological network databases, methods that can utilize this prior knowledge are needed and will offer biologists with a viable, more powerful alternative when analyzing RNA-seq data. RESULTS: We propose a three-state Markov Random Field (MRF) method that utilizes known biological pathways and interaction to improve sensitivity and specificity and therefore reducing false discovery rates (FDRs) when detecting differentially expressed genes from RNA-seq data. The method requires normalized count data (e.g. in Fragments or Reads Per Kilobase of transcript per Million mapped reads (FPKM/RPKM) format) as its input and it is implemented in an R package pathDESeq available from Github. Simulation studies demonstrate that our method outperforms the two-state MRF model for various sample sizes. Furthermore, for a comparable FDR, it has better sensitivity than DESeq, EBSeq, edgeR and NOISeq. The proposed method also picks more top Gene Ontology terms and KEGG pathways terms when applied to real dataset from colorectal cancer and hepatocellular carcinoma studies, respectively. Overall, these findings clearly highlight the power of our method relative to the existing methods that do not utilize prior knowledge of biological network. AVAILABILITY AND IMPLEMENTATION: As an R package at https://github.com/MalathiSIDona/pathDESeq. TO INSTALL THE PACKAGE TYPE: install_github("MalathiSIDona/pathDESeq",build_vignettes = TRUE). After installation, type vignette("pathDESeq") to access the vignette. CONTACT: a.salim@latrobe.edu.au. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Colorectal cancer atlas: An integrative resource for genomic and proteomic annotations from colorectal cancer cell lines and tissues.

In order to advance our understanding of colorectal cancer (CRC) development and progression, biomedical researchers have generated large amounts of OMICS data from CRC patient samples and representative cell lines. However, these data are deposited in various repositories or in supplementary tables. A database which integrates data from heterogeneous resources and enables analysis of the multidimensional data sets, specifically pertaining to CRC is currently lacking. Here, we have developed Colorectal Cancer Atlas (http://www.colonatlas.org), an integrated web-based resource that catalogues the genomic and proteomic annotations identified in CRC tissues and cell lines. The data catalogued to-date include sequence variations as well as quantitative and non-quantitative protein expression data. The database enables the analysis of these data in the context of signaling pathways, protein-protein interactions, Gene Ontology terms, protein domains and post-translational modifications. Currently, Colorectal Cancer Atlas contains data for >13 711 CRC tissues, >165 CRC cell lines, 62 251 protein identifications, >8.3 million MS/MS spectra, >18 410 genes with sequence variations (404 278 entries) and 351 pathways with sequence variants. Overall, Colorectal Cancer Atlas has been designed to serve as a central resource to facilitate research in CRC.

Autotransporter Adhesins in Escherichia coli Pathogenesis.

Most bacteria produce adhesion molecules to facilitate the interaction with host cells and establish successful infections. An important group of bacterial adhesins belong to the autotransporter (AT) superfamily, the largest group of secreted and outer membrane proteins in Gram-negative bacteria. AT adhesins possess diverse functions that facilitate bacterial colonisation, survival and persistence, and as such are often associated with increased bacterial fitness and pathogenic potential. In this review, we will describe AIDA-I type AT adhesins, which comprise the biggest and most diverse group in the AT family. We will focus on Escherichia coli proteins and define general aspects of their biogenesis, distribution, structural properties and key roles in infection.

Proteomic Profiling of Exosomes Secreted by Breast Cancer Cells with Varying Metastatic Potential.

Cancer cells actively release extracellular vesicles, including exosomes, into the surrounding microenvironment. Exosomes play pleiotropic roles in cancer progression and metastasis, including invasion, angiogenesis, and immune modulation. However, the proteome profile of exosomes isolated from cells with different metastatic potential and the role of these exosomes in driving metastasis remains unclear. Here, we conduct a comparative proteomic analysis of exosomes isolated from several genetically related mouse breast tumor lines with different metastatic propensity. The amount of exosomes produced and the extent of cancer-associated protein cargo vary significantly between nonmetastatic and metastatic cell-derived exosomes. Metastatic cell-derived exosomes contain proteins that promote migration, proliferation, invasion, and angiogenesis while the nonmetastatic cell-derived exosomes contain proteins involved in cell-cell/cell-matrix adhesion and polarity maintenance. The metastatic exosomes contain a distinct set of membrane proteins including Ceruloplasmin and Metadherin which could presumably aid in targeting the primary cancer cells to specific metastatic sites. Hence, it can be concluded that the exosomes contain different protein cargo based on the host cells metastatic properties and can facilitate in the dissemination of the primary tumors to distant sites.

Human intellectual disability genes form conserved functional modules in Drosophila.

Intellectual Disability (ID) disorders, defined by an IQ below 70, are genetically and phenotypically highly heterogeneous. Identification of common molecular pathways underlying these disorders is crucial for understanding the molecular basis of cognition and for the development of therapeutic intervention strategies. To systematically establish their functional connectivity, we used transgenic RNAi to target 270 ID gene orthologs in the Drosophila eye. Assessment of neuronal function in behavioral and electrophysiological assays and multiparametric morphological analysis identified phenotypes associated with knockdown of 180 ID gene orthologs. Most of these genotype-phenotype associations were novel. For example, we uncovered 16 genes that are required for basal neurotransmission and have not previously been implicated in this process in any system or organism. ID gene orthologs with morphological eye phenotypes, in contrast to genes without phenotypes, are relatively highly expressed in the human nervous system and are enriched for neuronal functions, suggesting that eye phenotyping can distinguish different classes of ID genes. Indeed, grouping genes by Drosophila phenotype uncovered 26 connected functional modules. Novel links between ID genes successfully predicted that MYCN, PIGV and UPF3B regulate synapse development. Drosophila phenotype groups show, in addition to ID, significant phenotypic similarity also in humans, indicating that functional modules are conserved. The combined data indicate that ID disorders, despite their extreme genetic diversity, are caused by disruption of a limited number of highly connected functional modules.

FunRich: An open access standalone functional enrichment and interaction network analysis tool.

As high-throughput techniques including proteomics become more accessible to individual laboratories, there is an urgent need for a user-friendly bioinformatics analysis system. Here, we describe FunRich, an open access, standalone functional enrichment and network analysis tool. FunRich is designed to be used by biologists with minimal or no support from computational and database experts. Using FunRich, users can perform functional enrichment analysis on background databases that are integrated from heterogeneous genomic and proteomic resources (>1.5 million annotations). Besides default human specific FunRich database, users can download data from the UniProt database, which currently supports 20 different taxonomies against which enrichment analysis can be performed. Moreover, the users can build their own custom databases and perform the enrichment analysis irrespective of organism. In addition to proteomics datasets, the custom database allows for the tool to be used for genomics, lipidomics and metabolomics datasets. Thus, FunRich allows for complete database customization and thereby permits for the tool to be exploited as a skeleton for enrichment analysis irrespective of the data type or organism used. FunRich (http://www.funrich.org) is user-friendly and provides graphical representation (Venn, pie charts, bar graphs, column, heatmap and doughnuts) of the data with customizable font, scale and color (publication quality).

Multi-substrate Metabolic Tracing Reveals Marked Heterogeneity and Dependency on Fatty Acid Metabolism in Human Prostate Cancer.

Cancer cells undergo metabolic reprogramming to meet increased bioenergetic demands. Studies in cells and mice have highlighted the importance of oxidative metabolism and lipogenesis in prostate cancer; however, the metabolic landscape of human prostate cancer remains unclear. To address this knowledge gap, we performed radiometric (14C) and stable (13C) isotope tracing assays in precision-cut slices of patient-derived xenografts (PDX). Glucose, glutamine, and fatty acid oxidation was variably upregulated in malignant PDXs compared with benign PDXs. De novo lipogenesis (DNL) and storage of free fatty acids into phospholipids and triacylglycerols were increased in malignant PDXs. There was no difference in substrate utilization between localized and metastatic PDXs and hierarchical clustering revealed marked metabolic heterogeneity across all PDXs. Mechanistically, glucose utilization was mediated by acetyl-CoA production rather than carboxylation of pyruvate, while glutamine entered the tricarboxylic acid cycle through transaminase reactions before being utilized via oxidative or reductive pathways. Blocking fatty acid uptake or fatty acid oxidation with pharmacologic inhibitors was sufficient to reduce cell viability in PDX-derived organoids, whereas blockade of DNL, or glucose or glutamine oxidation induced variable and limited therapeutic efficacy. These findings demonstrate that human prostate cancer, irrespective of disease stage, can effectively utilize all metabolic substrates, albeit with marked heterogeneity across tumors. We also confirm that fatty acid uptake and oxidation are targetable metabolic dependencies in human prostate cancer. IMPLICATIONS: Prostate cancer utilizes multiple substrates to fuel energy requirements, yet pharmacologic targeting of fatty acid uptake and oxidation reveals metabolic dependencies in localized and metastatic tumors.

A proteogenomic approach to map the proteome of an unsequenced pathogen - Leishmania donovani.

Visceral leishmaniasis or kala azar is the most severe form of leishmaniasis and is caused by the protozoan parasite Leishmania donovani. There is no published report on L. donovani genome sequence available till date, although the genome sequences of three related Leishmania species are already available. Thus, we took a proteogenomic approach to identify proteins from two different life stages of L. donovani. From our analysis of the promastigote (insect) and amastigote (human) stages of L. donovani, we identified a total of 22,322 unique peptides from a homology-based search against proteins from three Leishmania species. These peptides were assigned to 3711 proteins in L. infantum, 3287 proteins in L. major, and 2433 proteins in L. braziliensis. Of the 3711 L. donovani proteins that were identified, the expression of 1387 proteins was detectable in both life stages of the parasite, while 901 and 1423 proteins were identified only in promastigotes and amastigotes life stages, respectively. In addition, we also identified 13 N-terminally and one C-terminally extended proteins based on the proteomic data search against the six-frame translated genome of the three related Leishmania species. Here, we report results from proteomic profiling of L. donovani, an organism with an unsequenced genome.

Proteogenomic analysis of Candida glabrata using high resolution mass spectrometry.

Candida glabrata is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of C. glabrata using high resolution Fourier transform mass spectrometry with MS resolution of 60,000 and MS/MS resolution of 7500. On the basis of 32,453 unique peptides identified from 118,815 peptide-spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the C. glabrata genome. Further, searching the tandem mass spectra against a six frame translated genome database of C. glabrata resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts.

Comprehensive proteomic analysis of human bile.

Bile serves diverse functions from metabolism to transport. In addition to acids and salts, bile is composed of proteins secreted or shed by the hepatobiliary system. Although there have been previous efforts to catalog biliary proteins, an in-depth analysis of the bile proteome has not yet been reported. We carried out fractionation of non-cancerous bile samples using a multipronged approach (SDS-PAGE, SCX and OFFGEL) followed by MS analysis on an LTQ-Orbitrap Velos mass spectrometer using high resolution at both MS and MS/MS levels. We identified 2552 proteins - the largest number of proteins reported in human bile till date. To our knowledge, there are no previous studies employing high-resolution MS reporting a more detailed catalog of any body fluid proteome in a single study. We propose that extensive fractionation coupled to high-resolution MS can be used as a standard methodology for in-depth characterization of any body fluid. This catalog should serve as a baseline for the future studies aimed at discovering biomarkers from bile in gallbladder, hepatic, and biliary cancers.

Human Proteinpedia: a unified discovery resource for proteomics research.

Sharing proteomic data with the biomedical community through a unified proteomic resource, especially in the context of individual proteins, is a challenging prospect. We have developed a community portal, designated as Human Proteinpedia (http://www.humanproteinpedia.org/), for sharing both unpublished and published human proteomic data through the use of a distributed annotation system designed specifically for this purpose. This system allows laboratories to contribute and maintain protein annotations, which are also mapped to the corresponding proteins through the Human Protein Reference Database (HPRD; http://www.hprd.org/). Thus, it is possible to visualize data pertaining to experimentally validated posttranslational modifications (PTMs), protein isoforms, protein-protein interactions (PPIs), tissue expression, expression in cell lines, subcellular localization and enzyme substrates in the context of individual proteins. With enthusiastic participation of the proteomics community, the past 15 months have witnessed data contributions from more than 75 labs around the world including 2710 distinct experiments, >1.9 million peptides, >4.8 million MS/MS spectra, 150,368 protein expression annotations, 17,410 PTMs, 34,624 PPIs and 2906 subcellular localization annotations. Human Proteinpedia should serve as an integrated platform to store, integrate and disseminate such proteomic data and is inching towards evolving into a unified human proteomics resource.

RAPID: Resource of Asian Primary Immunodeficiency Diseases.

Availability of a freely accessible, dynamic and integrated database for primary immunodeficiency diseases (PID) is important both for researchers as well as clinicians. To build a PID informational platform and also as a part of action to initiate a network of PID research in Asia, we have constructed a web-based compendium of molecular alterations in PID, named Resource of Asian Primary Immunodeficiency Diseases (RAPID), which is available as a worldwide web resource at http://rapid.rcai.riken.jp/. It hosts information on sequence variations and expression at the mRNA and protein levels of all genes reported to be involved in PID patients. The main objective of this database is to provide detailed information pertaining to genes and proteins involved in primary immunodeficiency diseases along with other relevant information about protein-protein interactions, mouse studies and microarray gene-expression profiles in various organs and cells of the immune system. RAPID also hosts a tool, mutation viewer, to predict deleterious and novel mutations and also to obtain mutation-based 3D structures for PID genes. Thus, information contained in this database should help physicians and other biomedical investigators to further investigate the role of these molecules in PID.

Human Protein Reference Database--2009 update.

Human Protein Reference Database (HPRD--http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system--Human Proteinpedia (http://www.humanproteinpedia.org/)--through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15,000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome.

Mast Cell-Derived SAMD14 Is a Novel Regulator of the Human Prostate Tumor Microenvironment.

Mast cells (MCs) are important cellular components of the tumor microenvironment and are significantly associated with poor patient outcomes in prostate cancer and other solid cancers. The promotion of tumor progression partly involves heterotypic interactions between MCs and cancer-associated fibroblasts (CAFs), which combine to potentiate a pro-tumor extracellular matrix and promote epithelial cell invasion and migration. Thus far, the interactions between MCs and CAFs remain poorly understood. To identify molecular changes that may alter resident MC function in the prostate tumor microenvironment, we profiled the transcriptome of human prostate MCs isolated from patient-matched non-tumor and tumor-associated regions of fresh radical prostatectomy tissue. Transcriptomic profiling revealed a distinct gene expression profile of MCs isolated from prostate tumor regions, including the downregulation of SAMD14, a putative tumor suppressor gene. Proteomic profiling revealed that overexpression of SAMD14 in HMC-1 altered the secretion of proteins associated with immune regulation and extracellular matrix processes. To assess MC biological function within a model of the prostate tumor microenvironment, HMC-1-SAMD14+ conditioned media was added to co-cultures of primary prostatic CAFs and prostate epithelium. HMC-1-SAMD14+ secretions were shown to reduce the deposition and alignment of matrix produced by CAFs and suppress pro-tumorigenic prostate epithelial morphology. Overall, our data present the first profile of human MCs derived from prostate cancer patient specimens and identifies MC-derived SAMD14 as an important mediator of MC phenotype and function within the prostate tumor microenvironment.

The MURAL collection of prostate cancer patient-derived xenografts enables discovery through preclinical models of uro-oncology.

Preclinical testing is a crucial step in evaluating cancer therapeutics. We aimed to establish a significant resource of patient-derived xenografts (PDXs) of prostate cancer for rapid and systematic evaluation of candidate therapies. The PDX collection comprises 59 tumors collected from 30 patients between 2012-2020, coinciding with availability of abiraterone and enzalutamide. The PDXs represent the clinico-pathological and genomic spectrum of prostate cancer, from treatment-naïve primary tumors to castration-resistant metastases. Inter- and intra-tumor heterogeneity in adenocarcinoma and neuroendocrine phenotypes is evident from bulk and single-cell RNA sequencing data. Organoids can be cultured from PDXs, providing further capabilities for preclinical studies. Using a 1 x 1 x 1 design, we rapidly identify tumors with exceptional responses to combination treatments. To govern the distribution of PDXs, we formed the Melbourne Urological Research Alliance (MURAL). This PDX collection is a substantial resource, expanding the capacity to test and prioritize effective treatments for prospective clinical trials in prostate cancer.

Oral administration of bovine milk-derived extracellular vesicles induces senescence in the primary tumor but accelerates cancer metastasis.

The concept that extracellular vesicles (EVs) from the diet can be absorbed by the intestinal tract of the consuming organism, be bioavailable in various organs, and in-turn exert phenotypic changes is highly debatable. Here, we isolate EVs from both raw and commercial bovine milk and characterize them by electron microscopy, nanoparticle tracking analysis, western blotting, quantitative proteomics and small RNA sequencing analysis. Orally administered bovine milk-derived EVs survive the harsh degrading conditions of the gut, in mice, and is subsequently detected in multiple organs. Milk-derived EVs orally administered to mice implanted with colorectal and breast cancer cells reduce the primary tumor burden. Intriguingly, despite the reduction in primary tumor growth, milk-derived EVs accelerate metastasis in breast and pancreatic cancer mouse models. Proteomic and biochemical analysis reveal the induction of senescence and epithelial-to-mesenchymal transition in cancer cells upon treatment with milk-derived EVs. Timing of EV administration is critical as oral administration after resection of the primary tumor reverses the pro-metastatic effects of milk-derived EVs in breast cancer models. Taken together, our study provides context-based and opposing roles of milk-derived EVs as metastasis inducers and suppressors.

PathBuilder--open source software for annotating and developing pathway resources.

SUMMARY: We have developed PathBuilder, an open-source web application to annotate biological information pertaining to signaling pathways and to create web-based pathway resources. PathBuilder enables annotation of molecular events including protein-protein interactions, enzyme-substrate relationships and protein translocation events either manually or through automated importing of data from other databases. Salient features of PathBuilder include automatic validation of data formats, built-in modules for visualization of pathways, automated import of data from other pathway resources, export of data in several standard data exchange formats and an application programming interface for retrieving existing pathway datasets. AVAILABILITY: PathBuilder is freely available for download at http://pathbuilder.sourceforge.net/ under the terms of GNU lesser general public license (LGPL: http://www.gnu.org/copyleft/lesser.html). The software is platform independent and has been tested on Windows and Linux platforms. CONTACT: pandey@jhmi.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.